ISSN : 0975-2862
EISSN : 0975-9158
SEEMA THAKUR1*, RADHIKA NEGI2, PAYAL SHARMA3
1Scientist, ICAR-Krishi Vigyan Kendra, Kandaghat, 173213, Dr Yashwant Singh Parmar University of Horticulture and Forestry, Nauni, Solan, 173230, Himachal Pradesh
2Department of Vegetable Science, Dr Yashwant Singh Parmar University of Horticulture and Forestry, Nauni, Solan, 173230, Himachal Pradesh, India
3Department of Vegetable Science, Dr Yashwant Singh Parmar University of Horticulture and Forestry, Nauni, Solan, 173230, Himachal Pradesh, India
* Corresponding Author : thakurseema76@gmail.com
Received : 01-03-2019 Accepted : 15-03-2019 Published : 30-03-2019
Volume : 11 Issue : 3 Pages : 567 - 570
Genetics 11.3 (2019):567-570
Keywords : Bell Pepper, Germplasm
Academic Editor : Dr Muthana I Maleek, Dr Satish Baburao Shelke
Conflict of Interest : None declared
Acknowledgements/Funding : Authors are thankful to ICAR-Krishi Vigyan Kendra, Kandaghat, 173213, Dr Yashwant Singh Parmar University of Horticulture and Forestry, Nauni, Solan, 173230, Himachal Pradesh, India
Author Contribution : All authors equally contributed
Bell Pepper (Capsicum annuum L.) popularly known as sweet pepper, capsicum or Shimla Mirch is one of the important cash crops for temperate regions. Genetic restructuring of the bell pepper germplasm in public sector is the need of the hour. In this direction, the first and foremost step is the evaluation of the available germplasm so as to identify the potential genotype for their use either directly as varieties or as parent’s in future breeding programme. The determination of genetic variability and its partitioning into various components like genotypic, phenotypic and environmental variability is necessary to have an insight into the genetic nature of yield and its components which enable the breeders to adopt a suitable strategy and formulate a comprehensive breeding program, required for the necessary crop improvement. The correlation between different quantitative characters provides an idea of association that could be effectively exploited to formulate selection strategies for improving yield components. For any effective selection programme, it would be desirable to consider the relative magnitude of association of various characters with yield.
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